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remove duplicated tests from tests/stdlib_math.py
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extra_tests/snippets/stdlib_math.py

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@@ -291,94 +291,3 @@ def assertAllNotClose(examples, *args, **kwargs):
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assert math.fmod(-3.0, NINF) == -3.0
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assert math.fmod(0.0, 3.0) == 0.0
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assert math.fmod(0.0, NINF) == 0.0
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"""
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TODO: math.remainder was added to CPython in 3.7 and RustPython CI runs on 3.6.
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So put the tests of math.remainder in a comment for now.
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https://github.com/RustPython/RustPython/pull/1589#issuecomment-551424940
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"""
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# testcases = [
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# # Remainders modulo 1, showing the ties-to-even behaviour.
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# '-4.0 1 -0.0',
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# '-3.8 1 0.8',
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# '-3.0 1 -0.0',
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# '-2.8 1 -0.8',
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# '-2.0 1 -0.0',
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# '-1.8 1 0.8',
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# '-1.0 1 -0.0',
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# '-0.8 1 -0.8',
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# '-0.0 1 -0.0',
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# ' 0.0 1 0.0',
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# ' 0.8 1 0.8',
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# ' 1.0 1 0.0',
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# ' 1.8 1 -0.8',
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# ' 2.0 1 0.0',
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# ' 2.8 1 0.8',
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# ' 3.0 1 0.0',
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# ' 3.8 1 -0.8',
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# ' 4.0 1 0.0',
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# # Reductions modulo 2*pi
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# '0x0.0p+0 0x1.921fb54442d18p+2 0x0.0p+0',
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# '0x1.921fb54442d18p+0 0x1.921fb54442d18p+2 0x1.921fb54442d18p+0',
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# '0x1.921fb54442d17p+1 0x1.921fb54442d18p+2 0x1.921fb54442d17p+1',
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# '0x1.921fb54442d18p+1 0x1.921fb54442d18p+2 0x1.921fb54442d18p+1',
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# '0x1.921fb54442d19p+1 0x1.921fb54442d18p+2 -0x1.921fb54442d17p+1',
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# '0x1.921fb54442d17p+2 0x1.921fb54442d18p+2 -0x0.0000000000001p+2',
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# '0x1.921fb54442d18p+2 0x1.921fb54442d18p+2 0x0p0',
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# '0x1.921fb54442d19p+2 0x1.921fb54442d18p+2 0x0.0000000000001p+2',
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# '0x1.2d97c7f3321d1p+3 0x1.921fb54442d18p+2 0x1.921fb54442d14p+1',
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# '0x1.2d97c7f3321d2p+3 0x1.921fb54442d18p+2 -0x1.921fb54442d18p+1',
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# '0x1.2d97c7f3321d3p+3 0x1.921fb54442d18p+2 -0x1.921fb54442d14p+1',
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# '0x1.921fb54442d17p+3 0x1.921fb54442d18p+2 -0x0.0000000000001p+3',
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# '0x1.921fb54442d18p+3 0x1.921fb54442d18p+2 0x0p0',
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# '0x1.921fb54442d19p+3 0x1.921fb54442d18p+2 0x0.0000000000001p+3',
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# '0x1.f6a7a2955385dp+3 0x1.921fb54442d18p+2 0x1.921fb54442d14p+1',
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# '0x1.f6a7a2955385ep+3 0x1.921fb54442d18p+2 0x1.921fb54442d18p+1',
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# '0x1.f6a7a2955385fp+3 0x1.921fb54442d18p+2 -0x1.921fb54442d14p+1',
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# '0x1.1475cc9eedf00p+5 0x1.921fb54442d18p+2 0x1.921fb54442d10p+1',
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# '0x1.1475cc9eedf01p+5 0x1.921fb54442d18p+2 -0x1.921fb54442d10p+1',
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# # Symmetry with respect to signs.
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# ' 1 0.c 0.4',
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# '-1 0.c -0.4',
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# ' 1 -0.c 0.4',
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# '-1 -0.c -0.4',
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# ' 1.4 0.c -0.4',
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# '-1.4 0.c 0.4',
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# ' 1.4 -0.c -0.4',
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# '-1.4 -0.c 0.4',
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# # Huge modulus, to check that the underlying algorithm doesn't
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# # rely on 2.0 * modulus being representable.
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# '0x1.dp+1023 0x1.4p+1023 0x0.9p+1023',
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# '0x1.ep+1023 0x1.4p+1023 -0x0.ap+1023',
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# '0x1.fp+1023 0x1.4p+1023 -0x0.9p+1023',
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# ]
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# for case in testcases:
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# x_hex, y_hex, expected_hex = case.split()
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# # print(x_hex, y_hex, expected_hex)
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# x = float.fromhex(x_hex)
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# y = float.fromhex(y_hex)
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# expected = float.fromhex(expected_hex)
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# actual = math.remainder(x, y)
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# # Cheap way of checking that the floats are
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# # as identical as we need them to be.
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# assert actual.hex() == expected.hex()
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# # self.assertEqual(actual.hex(), expected.hex())
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# # Test tiny subnormal modulus: there's potential for
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# # getting the implementation wrong here (for example,
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# # by assuming that modulus/2 is exactly representable).
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# tiny = float.fromhex('1p-1074') # min +ve subnormal
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# for n in range(-25, 25):
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# if n == 0:
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# continue
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# y = n * tiny
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# for m in range(100):
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# x = m * tiny
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# actual = math.remainder(x, y)
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# actual = math.remainder(-x, y)

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